Forecasting the direction of Indonesia's consumer goods sector stock price movement using Fuzzy Kernel Robust C-Means

K. Takbiradzani, Z. Rustam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Investors have an intention to gain profit from every investment they made. A stock is one of the investment tools that could gain high profit. The stock has become one of the popular investment tools in Indonesia. Due to the complicated factors in the stock market, it's hard to obtain an accurate prediction model to foresee the stock price movement. If investors could foresee the movement of stock price, they will know what decision they made, whether it is to buy, hold or sell. Thus, this paper focused on the application of Fuzzy Kernel Robust C-Means in forecasting the direction of Indonesian stock price movement, specifically, on the consumer goods sector. There are seventeen technical indicators were calculated in this paper by using the historical stock data. The purpose of using Fuzzy Kernel Robust C-Means is it can show the robustness to the outlier. The stocks data that we will be using is from particular companies that listed on Indonesia Stock Exchange (IDX) in consumer goods sector. The outcome shows that the best model of the complete experiment with 100 % accuracy given with σ = 0.01 using 90 % training data.

Original languageEnglish
Title of host publicationProceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018
EditorsTerry Mart, Djoko Triyono, Ivandini T. Anggraningrum
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419155
DOIs
Publication statusPublished - 4 Nov 2019
Event4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018 - Depok, Indonesia
Duration: 30 Oct 201831 Oct 2018

Publication series

NameAIP Conference Proceedings
Volume2168
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018
CountryIndonesia
CityDepok
Period30/10/1831/10/18

Keywords

  • forecasting
  • Fuzzy Kernel Robust C-Means
  • prediction
  • stock price movement
  • technical indicators

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    Takbiradzani, K., & Rustam, Z. (2019). Forecasting the direction of Indonesia's consumer goods sector stock price movement using Fuzzy Kernel Robust C-Means. In T. Mart, D. Triyono, & I. T. Anggraningrum (Eds.), Proceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018 [020055] (AIP Conference Proceedings; Vol. 2168). American Institute of Physics Inc.. https://doi.org/10.1063/1.5132482